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用于定量表型分析的生物成像。

Bioimaging for quantitative phenotype analysis.

作者信息

Chen Weiyang, Xia Xian, Huang Yi, Chen Xingwei, Han Jing-Dong J

机构信息

Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China.

Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China.

出版信息

Methods. 2016 Jun 1;102:20-5. doi: 10.1016/j.ymeth.2016.01.017. Epub 2016 Feb 2.

Abstract

With the development of bio-imaging techniques, an increasing number of studies apply these techniques to generate a myriad of image data. Its applications range from quantification of cellular, tissue, organismal and behavioral phenotypes of model organisms, to human facial phenotypes. The bio-imaging approaches to automatically detect, quantify, and profile phenotypic changes related to specific biological questions open new doors to studying phenotype-genotype associations and to precisely evaluating molecular changes associated with quantitative phenotypes. Here, we review major applications of bioimage-based quantitative phenotype analysis. Specifically, we describe the biological questions and experimental needs addressable by these analyses, computational techniques and tools that are available in these contexts, and the new perspectives on phenotype-genotype association uncovered by such analyses.

摘要

随着生物成像技术的发展,越来越多的研究应用这些技术来生成大量的图像数据。其应用范围从模式生物的细胞、组织、生物体和行为表型的量化,到人类面部表型。基于生物成像的方法可自动检测、量化和描述与特定生物学问题相关的表型变化,为研究表型-基因型关联以及精确评估与定量表型相关的分子变化打开了新的大门。在这里,我们回顾基于生物图像的定量表型分析的主要应用。具体来说,我们描述了这些分析可解决的生物学问题和实验需求、这些背景下可用的计算技术和工具,以及此类分析所揭示的关于表型-基因型关联的新观点。

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